Abstract
Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator.
Highlights
Diffusion magnetic resonance imaging provides, completely non-invasively, unique insights into the complex microstructural architecture of the living human brain
We argue that an normalized mean square error (NMSE) of up to 30% due to signal extrapolation and reduced SNR at higher b-values for 3-shell high angular resolution diffusion imaging (HARDI) is not favorable for subsequent diffusion and microstructural parameter estimation
Our results show that compared to the dedicated CHARMED reference, compressed sensing theory (CS-DSI) allows for accurate FR parameter estimation that the standard 3-shell HARDI scheme applied in population imaging cannot provide
Summary
Diffusion magnetic resonance imaging (dMRI) provides, completely non-invasively, unique insights into the complex microstructural architecture of the living human brain. A whole range of mathematical representations (e.g., Basser et al, 1994; Jensen et al, 2005; Wedeen et al, 2005; Ozarslan et al, 2009 and biophysical models, e.g., Behrens et al, 2003; Assaf and Basser, 2005; Zhang et al, 2012), exists to characterize the diffusion signal as well as the underlying microstructure and to infer macroscopic brain connections from voxel-wise fiber orientation estimates This makes dMRI a powerful imaging modality to study in vivo pathological changes of diffusion in brain tissue and the influence of disease on the structural connectivity of brain white matter (WM). DMRI analysis techniques further influence the choice of the imaging protocol by imposing special requirements on the dMRI acquisitions for accurate data processing
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
